ROBUST REPEATABLE MONITORING WITH EIT
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Engineering
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Organisations
People |
ORCID iD |
Hugh McCann (Principal Investigator) |
Publications
Ahsan S T
(2017)
Distinguishability-to-noise ratio (DNR), a parameter to determine the discriminating capability of an EIT instrument
in GE-International Journal of Engineering Research
Crabb MG
(2014)
Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT.
in Physiological measurement
Liu S
(2020)
Time Sequence Learning for Electrical Impedance Tomography Using Bayesian Spatiotemporal Priors
in IEEE Transactions on Instrumentation and Measurement
Ouypornkochagorn T
(2023)
Towards continuous EIT monitoring for hemorrhagic stroke patients.
in Frontiers in physiology
Ouypornkochagorn T
(2019)
A Comparison of Bound-Constrained and Positivity-Constrained Optimization Method to Estimate Head Tissue Conductivities by Scalp Voltage Information
in International journal of electrical and computer engineering systems
Ouypornkochagorn T
(2015)
Tackling modelling error in the application of electrical impedance tomography to the head.
in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Ouypornkochagorn T
(2015)
Electrical Impedance Measurement of Cerebral Haemodynamics
Description | First demonstration of imaging of cerebral haemodynamics by Electrical Impedance Tomography. Demonstration of World-leading performance of EIT for lung imaging. |
Exploitation Route | Multiple. |
Sectors | Healthcare |
Description | To design further EIT systems (e.g. multi-frequency) with further sensitivity and utility. The methods and data analysis carried out in this prioject work have led to a fundamentally new capability, viz. to image human cerebral haemodynamics by EIT using scalp-mounted electrodes, as published in an IEEE Sensors paper in 2022. This is a world first. We have subsequently demonstrated (by simulation) that haemorrhagic stroke can be monitored continuously, as published in a Frontiers paper in 2023. Work is now underway with clinicians to apply this methodology to stroke patients. |
First Year Of Impact | 2022 |
Sector | Healthcare,Pharmaceuticals and Medical Biotechnology |
Impact Types | Societal |